This class put more emphases on applications instead of statisical theories. Upon completion of the class, students are expected to be able to:
Grading: Four sets of homework, each worth 15%. Final project 30%. Class participate 10%.
Lab: Bring laptop to the labs.
Here are some reading materials related to the class. It is NOT required to read them all, but it'll help you get better understanding of certain materials.
The final project could be (but not limited to) exploratory analysis, statistical modeling, or analytical software development for any type of genomic data. Some ideas of projects include:
Students need to submit a short report for the final project, as well as related programs. The report should NOT exceed 6 pages (single spacing, 11 point, 1 inch margin) with figures. There is no minimum page requirement.
|Date||Lecture Title||Description||Homework||Suggested Reading|
|8/29 (Wed)||Lecture 1: Introduction [PDF]||Brief introduction of molecular biology, high-throughput experiments, R and Bioconductor.||Wikipedia pages for gene, genome, microarray and sequencing.||9/3 (Mon)||Labor day, no class||9/5 (Wed)||Lab 1: Simple genomic analysis using R [PDF, R]||Exploratory analysis of human refseq genes.||Homework1||9/10 (Mon)||Lecture 2: Gene expression microarray I [PDF]||Experimental procedures and data pre-processing methods for Gene expression microarrays.||The microarray review article, RMA and GCRMA papers.||9/12 (Wed)||Lecture 3: Gene expression microarray II, tiling arrays. [PDF]||Differential expression from GE arrays. Batch effects.||SAM and Limma papers.||9/17 (Mon)||Lab 2: Analyzing gene expression array data from MAQC. [PDF][R]||Using gene expression microarrays generated by MAQC project, we will explore data produced from different array designs and compare to the gold standard. The gold standard Taqman data can be found at here.||Homework2||9/19 (Wed)||Lecture 4: Handling genome data using Bioconductor I [PDF][R]||Introduce Biostrings and BSgenome Bioconductor packages.||PLoS CB paper, Package Vignettes for Biostrings and BSgenome.||9/24 (Mon)||Lecture 5: Handling genome data using Bioconductor II [PDF][R]||Introduce GenomicRanges and GenomicFeatures Bioconductor packages.||PLoS CB paper, Package Vignettes for GenomicRanges and GenomicFeatures.||9/26 (Wed)||Lab 3: Analyzing human genome [PDF][R]||Study the sequence composition of human genome. Look at overlaps of CpG islands and gene promoters. List of CpG island can be downloaded at here.||Homework3||10/1 (Mon)||Lecture 6: Introduction to second generation sequencing [PDF]||Introduce second generation sequencing technologies and software for alignment, variant calling and visualization.||10/3 (Wed)||Lecture 7: RNA-seq [PDF]||Experimental procedure and data analysis for RNA-seq data. Normalization and differential expression detection. DEseq and edgeR Bioconductor package.||edgeR, DESeq, and cufflink papers||10/8 (Mon)||Fall break, no class||10/10 (Wed)||Lecture 8: ChIP-seq [PDF]||Experimental procedure of ChIP-seq. Peak calling methods. Comparison of multiple ChIP-seq. Joint analysis of ChIP-seq and RNA-seq.||MACS and PeakSeq papers||10/15 (Mon)||Lab 4: Handling second generation sequencing data, RNA- and ChIP-seq analyses [PDF][R]||This lab will practice the materials covered in three lectures. (1) sequence alignment with bowtie and manipulation with samtools and Rsamtools. (2) RNA-seq analysis using DEseq and edgeR. (3) Joint analysis of ChIP-seq and RNA-seq. Data can be dowload here.||Homework4||10/17 (Wed)||Lecture 9: Bisulfite sequencing [PDF]||Experimental procedure of bisulfite sequencing. Differential methylation. DNA methylation and protein binding.||BSmooth and DSS papers||10/22 (Mon)||Lecture 10: Single-cell sequencing [PDF]||Briefly introduce single-cell sequencing technologies and data analysis, with emphasis on single-cell RNA sequencing (scRNA-seq).||Monocle, Wanderlust, RaceID, and MAST papers|